Python SingleClusterEnvironment.deallocate方法代码示例

# 需要导入模块: from radical.ensemblemd import SingleClusterEnvironment [as 别名]
# 或者: from radical.ensemblemd.SingleClusterEnvironment import deallocate [as 别名]
    def test_pipeline_remote(self,cmdopt):
#if __name__ == "__main__":
        resource = cmdopt
        home = expanduser("~")
        try:

            with open('%s/workspace/EnsembleMDTesting/config.json'%home) as data_file:    
                  config = json.load(data_file)
            #resource='xsede.stampede'
            print "project: ",config[resource]['project']
            print "username: ", config[resource]['username'] 
            # Create a new static execution context with one resource and a fixed
            # number of cores and runtime.
            cluster = SingleClusterEnvironment(
                        resource=resource,
                        cores=1,
                        walltime=15,
                        #username='tg831932',
                        username=config[resource]['username'],
                        #project="TG-MCB090174",
                        #access_schema="ssh",
                        #queue="development",
                        project=config[resource]['project'],
                        access_schema = config[resource]['schema'],
                        queue = config[resource]['queue'],

                        database_url='mongodb://suvigya:[email protected]:51585',
                        database_name='rutgers_thesis',
                  )

            os.system('/bin/echo remote > input_file.txt')

            # Allocate the resources.
            cluster.allocate()

            # Set the 'instances' of the pipeline to 1. This means that 1 instance
            # of each pipeline step is executed.
            app = _TestPipeline(steps=1,instances=1)

            cluster.run(app)

            # Deallocate the resources. 
            cluster.deallocate()
            f = open("%s/workspace/EnsembleMDTesting/temp_results/remote_file.txt"%home)
            print "Name of file: ", f.name
            print "file closed or not: ", f.closed
            fname = f.readline().split()
            print "fname: ", fname
            assert fname == ['remote']
            f.close()
            os.remove("%s/workspace/EnsembleMDTesting/temp_results/remote_file.txt"%home)

        except EnsemblemdError, er:

            print "Ensemble MD Toolkit Error: {0}".format(str(er))
            raise # Just raise the execption again to get the backtrace

# 需要导入模块: from radical.ensemblemd import SingleClusterEnvironment [as 别名]
# 或者: from radical.ensemblemd.SingleClusterEnvironment import deallocate [as 别名]
      def test_copy_input_data_single(self):
#if __name__ == '__main__':

          #resource = 'local.localhost'
          try:

              with open('%s/config.json'%os.path.dirname(os.path.abspath(__file__))) as data_file:    
                    config = json.load(data_file)

                  # Create a new static execution context with one resource and a fixed
                  # number of cores and runtime.
              
              cluster = SingleClusterEnvironment(
                              resource='xsede.stampede',
                              cores=1,
                              walltime=15,
                              #username=None,
	    		      username='tg831932',
	    		      project='TG-MCB090174',
	    		      access_schema='ssh',
	    		      queue='development',

                              #project=config[resource]['project'],
                              #access_schema = config[resource]['schema'],
                              #queue = config[resource]['queue'],

                              database_url='mongodb://suvigya:[email protected]:51585/rutgers_thesis'
                        )

              os.system('/bin/echo passwd > input_file.txt')

                  # Allocate the resources.
              cluster.allocate(wait=True)

                  # Set the 'instances' of the pipeline to 1. This means that 1 instance
                  # of each pipeline step is executed.
      ##        app = _TestMyApp(instances=1,
      ##                         copy_directives="/etc/passwd",
      ##                         checksum_inputfile="passwd",
      ##                         download_output="CHKSUM_1"
      ##                         )
              app = _TestMyApp(steps=1,instances=1)
              cluster.run(app)
              f = open("./output_file.txt")
              print "Name of file: ", f.name
              print "file closed or not: ", f.closed
              fname = f.readline().split()
              print "fname: ", fname
              cluster.deallocate()
              assert fname == ['passwd']
              f.close()
              os.remove("./output_file.txt")

          except Exception as er:
              print "Ensemble MD Toolkit Error: {0}".format(str(er))
              raise # Just raise the execption again to get the backtrace

# 需要导入模块: from radical.ensemblemd import SingleClusterEnvironment [as 别名]
# 或者: from radical.ensemblemd.SingleClusterEnvironment import deallocate [as 别名]
    def test_sal(self,cmdopt):
#if __name__ == "__main__":

        resource = cmdopt
        home = expanduser("~")
        try:

            with open('%s/workspace/EnsembleMDTesting/config.json'%home) as data_file:    
                config = json.load(data_file)

            print 'Project: ',config[resource]['project']
            print 'Username: ',config[resource]['username']
     
           # Create a new static execution context with one resource and a fixed
            # number of cores and runtime.
            cluster = SingleClusterEnvironment(
                            resource=resource,
                            cores=1,
                            walltime=15,
                            username=config[resource]['username'],

                            project=config[resource]['project'],
                            access_schema = config[resource]['schema'],
                            queue = config[resource]['queue'],

                            database_url='mongodb://suvigya:[email protected]:51585/rutgers_thesis',
                            #database_name='myexps',
            )

            # Allocate the resources.
            cluster.allocate()
            randomsa = RandomSA(maxiterations=1, simulation_instances=1, analysis_instances=1)
            cluster.run(randomsa)
            cluster.deallocate()


            # After execution has finished, we print some statistical information
            # extracted from the analysis results that were transferred back.
            for it in range(1, randomsa.iterations+1):
                print "\nIteration {0}".format(it)
                ldists = []
                for an in range(1, randomsa.analysis_instances+1):
                    ldists.append(int(open("analysis-{0}-{1}.dat".format(it, an), "r").readline()))
                print "   * Levenshtein Distances: {0}".format(ldists)
                print "   * Mean Levenshtein Distance: {0}".format(sum(ldists) / len(ldists))
            assert os.path.isfile("%s/workspace/EnsembleMDTesting/E2E_test/analysis-1-1.dat"%home)
            os.remove("%s/workspace/EnsembleMDTesting/E2E_test/analysis-1-1.dat"%home)
        except EnsemblemdError, er:

            print "Ensemble MD Toolkit Error: {0}".format(str(er))
            raise # Just raise the execption again to get the backtrace

# 需要导入模块: from radical.ensemblemd import SingleClusterEnvironment [as 别名]
# 或者: from radical.ensemblemd.SingleClusterEnvironment import deallocate [as 别名]
def enmd_setup_run(request):
    from radical.ensemblemd import SingleClusterEnvironment
    try:
        sec = SingleClusterEnvironment(
            #resource="local.localhost",
            #cores=1,
            #walltime=1,
            resource="xsede.stampede",
            cores=1,
            walltime=1,
	    username='tg831932',
	    project='TG-MCB090174',
	    access_schema='ssh',
	    queue='development',
            database_url='mongodb://suvigya:[email protected]:51585',
            database_name='rutgers_thesis'
            )
        test = _TestRun(steps=1,instances=1)
        ret_allocate = sec.allocate()
        ret_run = sec.run(test)
        ret_deallocate = sec.deallocate()
    except Exception as e:
        #print ret_run
        raise
    return ret_allocate,ret_run,ret_deallocate

# 需要导入模块: from radical.ensemblemd import SingleClusterEnvironment [as 别名]
# 或者: from radical.ensemblemd.SingleClusterEnvironment import deallocate [as 别名]
    def test_all_pairs_remote(self,cmdopt):
#if __name__ == "__main__":


    # use the resource specified as argument, fall back to localhost
        resource = cmdopt
        home = expanduser("~")
        try:

            with open('%s/workspace/EnsembleMDTesting/config.json'%home) as data_file:    
                config = json.load(data_file)
            print 'project: ', config[resource]['project']
            print 'username: ',config[resource]['username']
            # Create a new static execution context with one resource and a fixed
            # number of cores and runtime.
            cluster = SingleClusterEnvironment(
                            resource=resource,
                            cores=1,
                            walltime=15,
                            username=config[resource]['username'],

                            project=config[resource]['project'],
                            access_schema = config[resource]['schema'],
                            queue = config[resource]['queue'],

                            database_url='mongodb://suvigya:[email protected]:51585',
                            database_name='rutgers_thesis',
            )

            # Allocate the resources.
            cluster.allocate()

            # For example the set has 5 elements.
            ElementsSet1 = range(1,2)
            randAP = _TestRandomAP(set1elements=ElementsSet1,windowsize1=1)

            cluster.run(randAP)

            cluster.deallocate()
            print "Pattern Execution Completed Successfully! Result files are downloaded!"
            assert os.path.isfile("./comparison_1_1.log")
            os.remove("./comparison_1_1.log")
            
        except EnsemblemdError, er:

            print "Ensemble MD Toolkit Error: {0}".format(str(er))
            raise # Just raise the execption again to get the backtrace

# 需要导入模块: from radical.ensemblemd import SingleClusterEnvironment [as 别名]
# 或者: from radical.ensemblemd.SingleClusterEnvironment import deallocate [as 别名]
def enmd_setup_run(request):
    from radical.ensemblemd import SingleClusterEnvironment
    try:
        sec = SingleClusterEnvironment(
            resource="local.localhost",
            cores=1,
            walltime=1,
            database_url='mongodb://suvigya:[email protected]:51585',
            database_name='rutgers_thesis'
            )
        test = _TestRun(steps=1,instances=1)
        ret_allocate = sec.allocate()
        ret_run = sec.run(test)
        ret_deallocate = sec.deallocate()
    except Exception as e:
        print ret_run
        raise
    return ret_allocate,ret_run,ret_deallocate

# 需要导入模块: from radical.ensemblemd import SingleClusterEnvironment [as 别名]
# 或者: from radical.ensemblemd.SingleClusterEnvironment import deallocate [as 别名]
def enmd_setup():
    from radical.ensemblemd import SingleClusterEnvironment
    try:
        sec = SingleClusterEnvironment(
            resource="local.localhost",
            cores=1,
            walltime=1,
            database_url='mongodb://suvigya:[email protected]:51585',
            database_name='rutgers_thesis'
            )
        ret_allocate = sec.allocate(wait=True)
        ret_deallocate = False
        ret_deallocate= sec.deallocate()

    except Exception as e:
        print 'test failed'
        raise

    return ret_allocate,ret_deallocate

# 需要导入模块: from radical.ensemblemd import SingleClusterEnvironment [as 别名]
# 或者: from radical.ensemblemd.SingleClusterEnvironment import deallocate [as 别名]
def enmd_setup():
    from radical.ensemblemd import SingleClusterEnvironment
    try:
        sec = SingleClusterEnvironment(
            resource="xsede.stampede",
            cores=1,
            walltime=1,
	    username='tg831932',
	    project='TG-MCB090174',
	    access_schema='ssh',
	    queue='development',
            database_url='mongodb://suvigya:[email protected]:51585',
            database_name='rutgers_thesis'
            )
        ret_allocate = sec.allocate(wait=True)
        ret_deallocate = False
        ret_deallocate= sec.deallocate()

    except Exception as e:
        print 'test failed'
        raise

    return ret_allocate,ret_deallocate

# 需要导入模块: from radical.ensemblemd import SingleClusterEnvironment [as 别名]
# 或者: from radical.ensemblemd.SingleClusterEnvironment import deallocate [as 别名]
                        database_url='mongodb://ec2-54-221-194-147.compute-1.amazonaws.com:24242',
                        database_name='myexps',
        )

        # Allocate the resources. 
        cluster.allocate()

        # Set the 'instances' of the pipeline to 16. This means that 16 instances
        # of each pipeline step are executed.
        #
        # Execution of the 16 pipeline instances can happen concurrently or
        # sequentially, depending on the resources (cores) available in the
        # SingleClusterEnvironment.
        ccount = CharCount(steps=3,instances=16)

        cluster.run(ccount)


        # Deallocate the resources. 
        cluster.deallocate()

        # Print the checksums
        print "\nResulting checksums:"
        import glob
        for result in glob.glob("cfreqs-*.sha1"):
            print "  * {0}".format(open(result, "r").readline().strip())

    except EnsemblemdError, er:

        print "Ensemble MD Toolkit Error: {0}".format(str(er))
        raise # Just raise the execption again to get the backtrace

# 需要导入模块: from radical.ensemblemd import SingleClusterEnvironment [as 别名]
# 或者: from radical.ensemblemd.SingleClusterEnvironment import deallocate [as 别名]
    def test_replica_exchange(self,cmdopt):
#if __name__ == "__main__":
        resource = cmdopt
        home = expanduser("~")
        try:

            with open('%s/workspace/EnsembleMDTesting/config.json'%home) as data_file:    
                config = json.load(data_file)

            print 'Project: ',config[resource]['project']
            print 'Username: ',config[resource]['username']
            # Create a new static execution context with one resource and a fixed
            # number of cores and runtime.

            workdir_local = os.getcwd()
            cluster = SingleClusterEnvironment(
                            resource=resource,
                            cores=1,
                            walltime=15,
                            username=config[resource]['username'],

                            project=config[resource]['project'],
                            access_schema = config[resource]['schema'],
                            queue = config[resource]['queue'],

                            database_url='mongodb://suvigya:[email protected]:51585/rutgers_thesis',
                            #database_name='myexps',
            )
            
            # Allocate the resources.
            cluster.allocate()

            # creating RE pattern object
            re_pattern = _TestRePattern(workdir_local)

            # set number of replicas
            re_pattern.replicas = 2
     
            # set number of cycles
            re_pattern.nr_cycles = 1

            # initializing replica objects
            replicas = re_pattern.initialize_replicas()

            re_pattern.add_replicas( replicas )

            # run RE simulation
            cluster.run(re_pattern, force_plugin="replica_exchange.static_pattern_1")

            cluster.deallocate()
            
            print "RE simulation finished!"
            print "Simulation performed {0} cycles for {1} replicas. In your working directory you should".format(re_pattern.nr_cycles, re_pattern.replicas)
            print "have {0} md_input_x_y.md files and {0} md_input_x_y.out files where x in {{0,1,2,...{1}}} and y in {{0,1,...{2}}}.".format( (re_pattern.nr_cycles*re_pattern.replicas), (re_pattern.replicas-1), (re_pattern.nr_cycles-1) )
            print ".md file is replica input file and .out is output file providing number of occurrences of each character."

            assert os.path.isfile("./md_input_0_0.out") and os.path.isfile("./md_input_1_0.out")
            os.remove("./md_input_0_0.out")
            os.remove("./md_input_0_0.md")
            os.remove("./md_input_1_0.out")
            os.remove("./md_input_1_0.md")

        except EnsemblemdError, er:

            print "Ensemble MD Toolkit Error: {0}".format(str(er))
            raise # Just raise the execption again to get the backtrace